Iterative learning control and initial value estimation for probe–drogue autonomous aerial refueling of UAVs

Dai, Xunhua; Quan, Quan; Ren, Jinrui; Cai, Kai-Yuan

doi:10.1016/j.ast.2018.09.034

Cited by 26 publications

(9 citation statements)

References 16 publications

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“…4 and Table . 5, we summarize some of the recently developed ILC algorithms in equations applied to UAVs and the strategies of ILC for more generalized and specific tasks, respectively. It is shown from Table IV, that in a large class of practical systems, such as autonomous aerial refueling based on terminal ILC [149] and [150], it is required that the output achieves perfect tracking at more than one defined time instants t " t i respectively. Therefore, it needs an extension of terminal ILC to solve problems which only require tracking of a number of critical positions at a subset of time instants.…”

Section: Figure 11mentioning

confidence: 99%

An Advanced Unmanned Aerial Vehicle (UAV) Approach via Learning-Based Control for Overhead Power Line Monitoring: A Comprehensive Review

Foudeh

Luk²,

Whidborne

2021

IEEE Access

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Detection and prevention of faults in overhead electric lines is critical for the reliability and availability of electricity supply. The disadvantages of conventional methods range from cumbersome installations to costly maintenance and from lack of adaptability to hazards for human operators. Thus, transmission inspections based on unmanned aerial vehicles (UAV) have been attracting the attention of researchers since their inception. This article provide a comprehensive review for the development of UAV technologies in the overhead electric power lines patrol process for monitoring and identifying faults, explores its advantages, and realizes the potential of the aforementioned method and how it can be exploited to avoid obstacles, especially when compared with the state-of-the-art mechanical methods. The review focuses on the development of advanced Learning Control strategies for higher manoeuvrability of the quadrotor. It also explores a suitable recharging strategies and motor control for improved mission autonomy.

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Section: Figure 11mentioning

confidence: 99%

An Advanced Unmanned Aerial Vehicle (UAV) Approach via Learning-Based Control for Overhead Power Line Monitoring: A Comprehensive Review

Foudeh

Luk²,

Whidborne

2021

IEEE Access

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“…Over the last few decades, a growing amount of research has focused on emerging 75 technologies for aircraft and aerospace systems (Wendel et al, 2006;Cacan et al, 2015;Puente et 76 al., 2018) and, specifically, on Unmanned Aerial Vehicles (Fabiani et al, 2007;Kontogiannis and 77 Ekaterinaris, 2013;Sazdovski et al, 2015;Ramasamy et al, 2016;Panagiotou et al, 2016;Goh et 78 al., 2017;Yu et al, 2017;Tyan et al, 2017;Hu et al, 2018;Oh and Kim, 2018;Dai et al, 2018;79 Saderla et al, 2018l;Liu et al, 2018;Mir et al, 2018;Wu et al, 2018;Jia et al, 2018;Radmanesh et al, 2018). Even though this type of aerial vehicles is primarily used for freight deliveries or military purposes, recent advances in automotive technology (Trancossi et al, 2017;Sudirja and Adhitya, 2018) have paved the way for the forthcoming penetration of an emerging transportation technology that further enhances automation and connectivity in urban mobility patterns without a priori requiring the concurrent interaction with the other components of the conventional transportation networks.…”

Section: Introductionmentioning

confidence: 99%

An exploratory empirical analysis of willingness to pay for and use flying cars

Eker¹,

Fountas

Anastasopoulos

2020

Aerospace Science and Technology

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From the early years of aviation, flying cars have constituted an appealing topic for science-fiction 35 scenarios. Currently, recent technological developments demonstrate that flying cars will be introduced in the traffic fleet over the next few years. Despite their forthcoming penetration in the automobile market, the level of anticipated acceptance from the traveling population has not been investigated yet in travel demand literature. This study aims -for the first time to the authors' knowledge -to provide a preliminary investigation of individuals' perceptions and expectations towards the adoption of flying cars. For this purpose, 692 individuals were questioned in the context of an online survey about their willingness to pay for and willingness to use flying cars for various pricing and trip scenarios, as well as about the benefits and concerns that will arise from the introduction of flying cars in the traffic fleet. To understand the determinants of individuals' expectations, their willingness to pay for and use flying cars was statistically modeled, by employing a grouped random parameters bivariate probit framework, which accounts for multiple 46 layers of unobserved heterogeneity in the respondent's decision-making process. The statistical analysis revealed that various individual-specific socio-demographic, behavioral and driving attributes, as well as individuals' attitudinal perspectives towards the cost, safety, security and environmental implications of the flying cars, affect their willingness to adopt this emerging transportation technology. Despite the current limited awareness about the operation of flying cars, the findings of this study can provide insights regarding critical challenges that should be addressed by policymakers, legislative companies, and manufacturing companies after the introduction of flying cars in the traffic fleet.

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“…This concept was first proposed in Uchiyama (1978). Nowadays, it has become an important branch of intelligence control and it is widely used in practical systems, such as ethanol fermentation processes (Lin et al, 2019), robot manipulator (Bouakrif and Zasadzinski, 2018), autonomous aerial refueling (Dai et al, 2018) and spacecraft attitude control (Hu et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

A data-driven approach for trajectory-based aircraft operation with controlled time of arrival and along-track wind effects

Jiang

Hou

2020

Transactions of the Institute of Measurement and Control

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Trajectory-based aircraft operation and control is one of the hot issues in air traffic management. However, the accurate mechanism modeling of aircraft is tough work, and the operation data have not been effectively utilized in many studies. So, in this work, we apply the model-free adaptive iterative learning control method to address the time-of-arrival control problem in trajectory-based aircraft operation. This problem is first formulated into a trajectory tracking problem with along-track wind disturbance. Through rigorous analysis, it is shown that this method, combined with point-to-point iterative learning control (ILC) strategy, can effectively deal with the arrival time control problem with multiple time constraints. Then, the terminal ILC strategy is applied, aiming to resolve the same problem with a time constraint at the end point. Compared with the PID (Proportional Integral Derivative) type ILC, the proposed method improves control performance by 11.15% in root mean square of tracking error and 9.32% in integral time absolute error. The sensitivity and flexibility of the data-driven approach is further verified through numerical simulations.

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Iterative learning control and initial value estimation for probe–drogue autonomous aerial refueling of UAVs

Cited by 26 publications

References 16 publications

An Advanced Unmanned Aerial Vehicle (UAV) Approach via Learning-Based Control for Overhead Power Line Monitoring: A Comprehensive Review

An Advanced Unmanned Aerial Vehicle (UAV) Approach via Learning-Based Control for Overhead Power Line Monitoring: A Comprehensive Review

An exploratory empirical analysis of willingness to pay for and use flying cars

A data-driven approach for trajectory-based aircraft operation with controlled time of arrival and along-track wind effects

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